1. Field of the Invention
The present invention relates to an access log analyzer for analyzing an access log of a server, and in particular, to an access log analyzer for, for example, statistically analyzing an access status of a Web server, which is disclosed on the Internet, so as to be used as a marketing tool for determining the needs of users, for component optimization, and the like.
2. Description of the Related Art
A conventional access log analyzer acquires an access log from a Web server so as to analyze the contents of the acquired access log for totaling the number of hits for each Web page or for each referrer. The number of hits is used to determine the usage of a Web site, for comparison between a number of sites, and the like.
For displaying the results of such analysis, a graph or a table is mainly used. An absolute value is generally represented by a bar chart, whereas a rate is generally represented by a pie chart.
However, since such a conventional access log analyzer basically uses a total number of hits as means of analyzing data, important data may be buried in a large amount of data in some cases.
For example, when the number of hits of the current day is to be evaluated, a change in the number of hits in comparison with the previous number of hits is more important than an absolute value of the number of hits itself. However, since a conventional access log analyzer merely displays an absolute value of the number of hits as a daily change, useful information turns out to be buried in some cases.
Moreover, a difference between the N-th rank and the N+1-th rank is not constant in ranking. Therefore, if the first ranking page is a “clear winner” outdistancing the others, a usual page may rank second in some cases. Furthermore, even if there is a page having a considerably increasing number of hits even though the number is small in absolute number, such a page is buried by a page constantly having a large number of hits.
On the other hand, although the use of a graph or a table is effective to allow easy viewing of a large amount of data as a presentation method, the graph or table merely shows the result of the adding up all of the hits in an easy-to-view manner. Therefore, what the graph or table indicates is required to be read by a user.
In particular, if the number of survey items is increased, the number of graphs or tables is correspondingly increased so as to become enormous. Accordingly, it is difficult to find out useful information from an enormous number of graphs or tables. As a result, the result of analysis is not fully utilized in some cases.
More specifically, assuming that a Web site is evaluated at three steps, from “totaling,” “analysis” to “examination for a next strategy,” only the first step “totaling” is performed in a conventional access log analyzer. An important “analysis” process is required to be manually done based on an enormous amount of data. As a result, there is a problem that a satisfactory result is not obtained in many cases.